Aram Davtyan

I am a Ph.D. student in the Computer Vision Group at the University of Bern, supervised by Prof. Dr. Paolo Favaro. I received my Specialist degree in Fundamental Mathematics and Mechanics at the Lomonosov Moscow State University in 2020. I also graduated from the Yandex School of Data Analysis in 2018. My topics of interest include Machine Learning, Computer Vision, Deep Learning and Generative Modeling.

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Publications

Enabling Visual Composition and Animation in Unsupervised Video Generation

Aram Davtyan, Sepehr Sameni, Björn Ommer, Paolo Favaro

arXiv, 2024

A model to compose and animate scenes from sparse sets of visual features.

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Learn the Force We Can: Enabling Sparse Motion Control in Multi-Object Video Generation

Aram Davtyan, Paolo Favaro

AAAI, 2024

A model to animate single frames with sparse motion control.

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Multi-View Unsupervised Image Generation with Cross Attention Guidance

Llukman Cerkezi, Aram Davtyan, Sepehr Sameni, Paolo Favaro

arXiv, 2023

Single image to novel view synthesis without any supervision.

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Efficient Video Prediction via Sparsely Conditioned Flow Matching

Aram Davtyan, Sepehr Sameni, Paolo Favaro

ICCV, 2023

Conditioning only on a few randomly chosen past frames at each denoising step of flow matching results into a more efficient training procedure.

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Controllable Video Generation through Global and Local Motion Dynamics

Aram Davtyan, Paolo Favaro

ECCV, 2022

A model to discover agents' action spaces from a dataset of videos in an unsupervised way. The action spaces are decomposed into global (2D shifts) and local (discrete) actions.

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KOALA: A Kalman Optimization Algorithm with Loss Adaptivity

Aram Davtyan, Sepehr Sameni, Llukman Cerkezi, Givi Meishvili, Adam Bielski, Paolo Favaro

AAAI, 2022

A neural network optimization algorithm based on Kalman filtering.

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